CN111030779B - Method for optimizing non-rate code degree distribution under compressed transmission of cloud access network - Google Patents

Method for optimizing non-rate code degree distribution under compressed transmission of cloud access network Download PDF

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CN111030779B
CN111030779B CN201911258777.7A CN201911258777A CN111030779B CN 111030779 B CN111030779 B CN 111030779B CN 201911258777 A CN201911258777 A CN 201911258777A CN 111030779 B CN111030779 B CN 111030779B
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CN111030779A (en
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张昱
范哲浩
孟利民
李�昊
彭宏
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Zhejiang University of Technology ZJUT
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0041—Arrangements at the transmitter end
    • H04L1/0042—Encoding specially adapted to other signal generation operation, e.g. in order to reduce transmit distortions, jitter, or to improve signal shape
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0047—Decoding adapted to other signal detection operation
    • H04L1/005—Iterative decoding, including iteration between signal detection and decoding operation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0061—Error detection codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0071—Use of interleaving
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/06—Optimizing the usage of the radio link, e.g. header compression, information sizing, discarding information
    • H04W28/065—Optimizing the usage of the radio link, e.g. header compression, information sizing, discarding information using assembly or disassembly of packets
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/08—Access point devices
    • H04W88/085—Access point devices with remote components
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a method for optimizing the distribution of a non-rate code degree under the compression transmission of a cloud access network, which is characterized by comprising the following steps: optimizing degree distribution adopted by no-rate coding at a user according to the network channel state and the RRH signal compression ratio; the user carries out non-rate coding on the original information according to degree distribution, and the code words are sent to each RRH covering the user after being modulated; the RRH firstly preprocesses the received signal to become a baseband signal, and then carries out quantization coding compression sending on the signal; and the BBU receives the quantized compressed signals sent by each RRH through the high-speed link, decodes the quantized compressed signals to recover the quantized signals, and finally decodes the quantized signals on a no-rate decoding graph by using a belief propagation algorithm to recover the user information. In the method for optimizing the degree, the degree distribution designed by the invention is better improved in the system throughput in a single-user uplink system of the cloud access network.

Description

Method for optimizing non-rate code degree distribution under compressed transmission of cloud access network
Technical Field
The invention relates to the technical field of wireless communication, in particular to a method for optimizing the distribution of a non-rate code degree under the compression transmission of a cloud access network.
Background
With the development of communication services, the number of base stations is increasing, and the acquisition of the station address is becoming more difficult. Wherein a cloud access network (C-RAN) may solve this problem to some extent.
A deployment mode of a cloud access network (C-RAN) is that a remote radio unit (RRH) and a baseband processing unit (BBU) of a traditional base station are separately deployed, the RRH is closer to a user, and each BBU is backward centralized into a central cloud computing resource pool to be responsible for processing baseband signals, so that unified and flexible management and control of the network can be realized. The forward link is a high-speed link (such as optical fiber and millimeter wave) supporting Gbps magnitude and less than 0.1ms delay, and is responsible for connecting a BBU pool and a large number of RRHs. Compared with the traditional RAN architecture, the C-RAN can efficiently solve the problems that network transmission resources cannot meet user requirements, network deployment and operation costs are increased year by year, energy consumption is increased year by year and the like. All base station signals in the C-RAN are processed uniformly by a BBU pool at the rear end, and the structure is favorable for implementation of interference coordination and a multi-point cooperation algorithm. The expansion network only needs to arrange new RRHs and lay optical fibers, and the cost is less than that of erecting a base station with a complete BBU. Because the signal processing is unified in the BBU pool and is cooled by the unified cooling equipment, and the BBU resources can be more flexibly allocated to adapt to the change of network flow, the energy consumption is greatly reduced.
The rate of the rateless code changes adaptively according to the change of the channel, and only the ACK signal fed back by the decoding end after being successfully decoded needs to be received to stop sending the code word, so that the signaling overhead is reduced, and the system loss caused by the feedback delay of the ACK signal can be effectively relieved. The transmitting end does not need to know the channel state, and the optimized rateless code can still have the performance close to the channel capacity. These characteristics of rateless codes make them suitable for use in transport mechanisms in cloud access networks. The research about the rateless code mainly comprises degree distribution design, decoding method design and the like, wherein degree distribution functions are directly related to the performance of the rateless code, the decoding success rate, the decoding overhead, the decoding complexity and the like are determined, and the key point of designing the rateless code is to construct a proper degree distribution function.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a reasonable-design method for optimizing the distribution of the non-rate code degrees under the compression transmission of the cloud access network.
The technical scheme of the invention is as follows:
a method for optimizing the distribution of the non-rate code degrees under the compression transmission of a cloud access network is characterized by comprising the following steps:
1) optimizing degree distribution adopted by no-rate coding at a user according to the network channel state and the RRH signal compression ratio;
2) the user carries out non-rate coding on the original information according to degree distribution, and the code words are modulated and then sent to each RRH covering the user; the RRH firstly preprocesses the received signal to become a baseband signal, and then carries out quantization coding compression sending on the signal; and the BBU receives the quantized compressed signals sent by each RRH through the high-speed link, decodes the quantized compressed signals to recover the quantized signals, and finally decodes the quantized signals on a no-rate decoding graph by using a belief propagation algorithm to recover the user information.
The method for optimizing the distribution of the non-rate code degrees under the compression transmission of the cloud access network is characterized in that the step 1) specifically comprises the following steps:
1.1) for the l-th round of decoding at the BBU, the LT input node transmits LLR information to the LDPC code graph check node, and the carried external information is as follows:
Figure BDA0002311027600000021
in the formula
Figure BDA0002311027600000022
Is the average extrinsic information, alpha, passed from the output node to the input node for the l-1 st iteration LTiFor the ratio of input nodes in the LT decoding diagram with degree i, dvInputting the maximum degree of a node for an LT code diagram, wherein J is an external information function carried by a message meeting symmetric Gaussian distribution;
for a message obeying a symmetric gaussian distribution with mean τ and variance 2 τ, the extrinsic information contained is:
Figure BDA0002311027600000023
the extrinsic information returned by the LDPC check node to the LT input node is:
Figure BDA0002311027600000024
xi in the formulaiIs the variable node proportion with degree i in the LDPC code graph,
Figure BDA0002311027600000025
is the proportion of edges connected with a check node of degree j in the LDPC code graph, d'vIs LDPC code graph variable node maximum degree, d'cChecking the maximum degree of the node for the LDPC code graph;
the external information that the LT input node transmits a message to the output node is:
Figure BDA0002311027600000026
in the formula
Figure BDA0002311027600000027
Is the proportion of edges connected to degree i input nodes, dvIs the maximum degree of the input node;
finally, the extrinsic information returned by the LT output node corresponding to the signal with the quantization bit a to the LT input node is:
Figure BDA0002311027600000031
in the formula of omegadRepresenting the proportion of edges connected to the degree dsout node,
Figure BDA0002311027600000032
Ia,γ＝J(ALLRi) Log likelihood ratio average ALLR of signal with quantization bit number a under signal-to-noise ratio gammaaThe amount of information carried, wherein:
Figure BDA0002311027600000033
where a ═ b or a ═ b +1, the average extrinsic information returned by all LT output nodes to the LT input node is:
Figure BDA0002311027600000034
in the formula YrThe compression rate of the corresponding code word quantization bit number in the quantizer is shown, b is the quantization bit number, r is 1,2 …, b, and the equations (6) and (7) are substituted into (9) to obtain the compression rate of each iteration
Figure BDA0002311027600000035
Update, which can be expressed as a function Φ (·):
Figure BDA0002311027600000036
in the formula
Figure BDA0002311027600000037
Average degree of input nodes, { omega, { for LT code graphdThe coefficient of the degree distribution of the edge of the LT output node;
1.2) defining the channel gains of 2 links as a vector
Figure BDA0002311027600000038
The situation of different link values h is expressed as W vectors
Figure BDA0002311027600000039
Vector ΓiIs defined as Pr (Γ)i) The joint optimization problem is listed below:
Figure BDA00023110276000000310
Figure BDA0002311027600000041
where epsilon is a small amount greater than zero,
Figure BDA0002311027600000042
the minimum threshold for the outer information to be correctly decoded,
Figure BDA0002311027600000043
is the channel gain gammaiThe lower signal-to-noise ratio is the theoretical capacity of a Gaussian channel with gamma; fixing the optimization problem (11)
Figure BDA0002311027600000044
The degree distribution omega (x) of the edge can be solved by a linear programming solution,
Figure BDA0002311027600000045
finding the average degree of LT input nodes by an exhaustion method;
1.3) by the formula
Figure BDA0002311027600000046
And (5) converting to obtain the optimal rate-free code degree distribution omega (x).
The method for optimizing the distribution of the non-rate code degrees under the compression transmission of the cloud access network is characterized in that the step 2) specifically comprises the following steps:
2.1) the channel from the user to the RRH is block fading and remains unchanged in a round of received code word, a single user in the system transmits uplink to two RRHs, the user uses the original information as the precoding without rate code by the LDPC precoder in sequence, and then passes through the LT encoder, and according to the LT code degree distribution Ω (x) ═ Ω1x+Ω2x2+...+ΩDxD，ΩkD is the probability of degree k, randomly selecting a degree k for each coded bit c, selecting k values with equal probability from all precodes, performing modulo-two summation on the selected k precoded bits to generate a rateless code c, and continuously generating the rateless code c according to the steps1,c2,……,cN；
2.2) mapping the bits 0 and 1 without rate codes into a sending symbol x according to the actual modulation mode1,x2,……,xNSending to each RRH covering the user through an antenna;
2.3) the preprocessor of each RRH preprocesses the received signal to obtain a baseband signal: y isi＝hix+niWherein h isiRepresenting source to RRHiChannel gain coefficient of the link between, niRepresents RRHiReceiving noise; the signal is then quantized by the quantizer of the RRH according to the forward link capacity b ratio between the RRH and BBUBit/symbol, the number of quantization levels satisfies 2M-2bWhere b is the quantization bit, the quantization interval is Δ, and the quantization threshold is
Figure BDA0002311027600000051
The quantized signal is
Figure BDA0002311027600000052
The quantization rule is as follows:
Figure BDA0002311027600000053
in the above formula q-M，qk，qMFinger quantized signal
Figure BDA0002311027600000054
Actual quantization level value of;
2.4) each RRH converts the N quantized signals obtained in step 2.3) into binary, b-bit RRHs1The compression rate of the corresponding code word quantization bit number is YrR is 1,2 …, b; the remaining capacity is calculated from the system forward link transmission capacity b
Figure BDA0002311027600000055
Random selection among N quantized signals
Figure BDA0002311027600000056
The signals are quantized by one more bit, and all the signals are sent to the BBU through a high-speed link;
2.5) BBU decoding is divided into two steps, firstly, the compressed quantized signal is decoded to recover RRH1The quantized signal of (a);
2.6) BBU decoding the second step is based on the decompressed quantized signal and the directly transmitted RRH2The quantized signal decodes the user's codeword. User rateless code ciEqual probability is taken as 0 and 1, the quantization signal uploaded to the BBU by the jth RRH is
Figure BDA0002311027600000057
The soft demodulator of BBU outputs LLR of ith bit as:
Figure BDA0002311027600000058
RRH (resistive random access memory)1And RRH2After the LLRs corresponding to the quantized signals are combined, the LLR of the ith bit is as follows:
Figure BDA0002311027600000059
in the formula,. DELTA.kTo quantize the level qkThe corresponding quantization interval, a is equal to b or b +1,
Figure BDA00023110276000000510
is the variance of Gaussian noise at each RRH, hjIs the link channel gain;
the BBU is subjected to iterative decoding on a rateless code graph, the 0 th round of iterative decoding is carried out, the initial LLR of an input node i in the decoding graph is 0, the initial LLR of an output node in the decoding graph is LLR (i), wherein the initial LLR of the output node in the decoding graph is LLR (i)
Figure BDA0002311027600000061
To quantize the number of bits as b +1,
Figure BDA0002311027600000062
is the number of quantization bits b;
in the first iteration, messages are transmitted from an LT input node to an LDPC check node, the LDPC check node transmits the messages back to the LT input node, the LT input node transmits the messages to an LT output node, and finally the LT output node transmits the messages and LLRs (Log/Log) obtained by calculation according to bit quantization values of corresponding code words back to the LT input node; when the LLR mean value of the input node of the round exceeds the decoding threshold x of the LDPCpThen, iterative decoding is carried out on the LDPC precoding code graph independently;
performing iteration decoding on the 0 th round of the LDPC precoding subgraph, and transmitting LLR (log likelihood ratio) of the input node to the LDPC by the LDPC variable node in the last round of iteration; in the first iteration, the LDPC variable node transmits a message to the LDPC check node, and then the message is transmitted to the LDPC variable node from the LDPC check node;
judging the log-likelihood ratio information LLR(s) of the bit s, judging the information bit s as 0 if the LLR(s) is greater than 0, otherwise judging the information bit s as 1, continuing iteration if the decoding is incorrect according to a judgment output result, and ending the decoding if the decoding is correct or the maximum iteration time t is reached.
The invention has the beneficial effects that: according to the method for optimizing the distribution of the degree of the rateless codes under the cloud access network compression transmission, the optimized rate-less code output node degree distribution under the block attenuation has better error code performance under the same transmission code word compared with the optimal degree under the deletion channel or other channels, and meanwhile the throughput of the system is better improved.
Drawings
Fig. 1 is a schematic diagram of uplink transmission from a single user to two RRHs in a cloud access network;
FIG. 2 is a graph of rateless code decoding;
fig. 3 is a graph comparing system throughput without rate code optimization under compressed transmission in the conventional method.
Detailed Description
The invention is further described with reference to the drawings and examples, but the scope of protection is not limited thereto:
referring to FIGS. 1-3: the method for optimizing the distribution of the non-rate code degrees under the compression transmission of the cloud access network specifically comprises the following steps: optimizing degree distribution adopted by no-rate coding at a user according to a network channel state and a Radio Remote Head (RRH) signal compression ratio, carrying out no-rate coding on original information by the user according to the degree distribution, and modulating and sending code words to each RRH covering the user; the RRH firstly preprocesses the received signal to become a baseband signal, and then carries out quantization coding compression sending on the signal; and a baseband processing unit (BBU) receives the quantized compressed signals transmitted by each RRH through the high-speed link, decodes the quantized compressed signals to recover the quantized signals, and finally decodes the quantized signals on a no-rate decoding graph by using a belief propagation algorithm to recover user information.
The transmission method comprises the following specific steps:
1) the channel from the user to the RRH is block fading and is kept unchanged in a round of receiving code words, and a single user in the system transmits uplink to two RRHs; and the user S carries out rateless coding on the original information, wherein the rateless code is formed by cascading an LDPC code with the outer code rate of 0.95 and an LT code of the inner code part.
1.1) a first step of coding, namely selecting an LDPC codebook with a code rate of 0.95 and converting original information s0,s1,……,skEncoding into LDPC codewords b1,b2,……,bn；
1.2) a second step of coding, n LDPC codewords b1,b2,……,bnPerforming LT coding according to LT code degree distribution omega (x) ═ omega1x+Ω2x2+...+ΩDxD，ΩkD is the probability of degree k, randomly selecting a degree k for each coded bit c, selecting k values with equal probability from all precodes, performing modulo-two summation on the selected k precoded bits to generate a rateless code c, and continuously generating the rateless code c according to the steps1,c2,……,cN；
2) Rateless code c1,c2,……,cNBefore accessing the channel, it is firstly modulated by Binary Phase Shift Keying (BPSK) to obtain the mapped transmission sequence x1,x2,……,xNThen, the sending sequence is accessed to the channel and sent out, the sending sequence is not fixed continuously in length, and each length corresponds to a corresponding code rate;
3) the preprocessor of each RRH preprocesses the received signal to obtain a baseband signal: y isi＝hix+niWherein h isiRepresenting source to RRHiChannel gain coefficient of the link between, niRepresents RRHiTo receive noise. Then, the quantizer of the RRH quantizes the signal, and the number of quantization levels satisfies 2M-2 according to the forward link capacity R bit/symbol between the RRH and the BBUbWhere b is a quantization bit with the value R, the quantization interval is Δ, and the quantization threshold is
Figure BDA0002311027600000071
The quantized signal is
Figure BDA0002311027600000072
The quantization rule is as follows:
Figure BDA0002311027600000073
in the above formula q-M，qk，qMFinger quantized signal
Figure BDA0002311027600000074
Actual quantization level value of;
4) each RRH converts the N quantization signals obtained in the step 3) into binary system of b bits, RRH1The compression rate of the corresponding code word quantization bit number is YrAnd r is 1,2 …, b. The remaining capacity is calculated from the system forward link transmission capacity b
Figure BDA0002311027600000081
Random selection among N quantized signals
Figure BDA0002311027600000082
The signals are quantized by one more bit, and all the signals are sent to the BBU through a high-speed link;
5) the BBU decoding is divided into two steps, firstly, the compressed quantized signal is decoded to recover the RRH1The quantized signal of (2).
6) The second step of BBU decoding is based on the decompressed quantized signal and the direct-transmitted RRH2The quantized signal decodes the user's codeword. User rateless code ciEqual probability is taken as 0 and 1, the quantization signal uploaded to the BBU by the jth RRH is
Figure BDA0002311027600000083
The soft demodulator of the BBU outputs a log-likelihood ratio (LLR) of the ith bit as:
Figure BDA0002311027600000084
RRH (red-green-blue)1And RRH2After the LLRs corresponding to the quantized signals are combined, the LLR of the ith bit is (the user adopts BPSK modulation, and the transmission power is normalized):
Figure BDA0002311027600000085
in the formula,. DELTA.kTo quantize the level qkThe corresponding quantization interval, a is equal to b or b +1,
Figure BDA0002311027600000086
is the variance of Gaussian noise at each RRH, hjIs the link channel gain.
The BBU carries out iterative decoding on the rateless code graph; and in the 0 th iteration decoding, the initial LLR of the input node i in the decoding graph is 0, and the initial LLR of the output node in the decoding graph is LLR (i), wherein
Figure BDA0002311027600000087
To quantize the number of bits as b +1,
Figure BDA0002311027600000088
is the number of quantization bits b.
In the first iteration, messages are transmitted from an LT input node to an LDPC check node, the LDPC check node transmits the messages back to the LT input node, the LT input node transmits the messages to an LT output node, and finally the LT output node transmits the messages and LLRs (Log/Log) obtained by calculation according to bit quantization values of corresponding code words back to the LT input node; when the LLR mean value of the input node of the round exceeds the decoding threshold x of the LDPCpAnd then performing iterative decoding on the LDPC precoding code graph independently.
Performing iteration decoding on the 0 th round of the LDPC precoding subgraph, and transmitting LLR (log likelihood ratio) of the input node to the LDPC by the LDPC variable node in the last round of iteration; in the first iteration, the LDPC variable node transmits the message to the LDPC check node, and then the message is transmitted from the LDPC check node to the LDPC variable node.
Judging the log-likelihood ratio information LLR(s) of the bit s, judging the information bit s as 0 if the LLR(s) is greater than 0, otherwise judging the information bit s as 1, continuing iteration if the decoding is incorrect according to a judgment output result, and ending the decoding if the decoding is correct or the maximum iteration time t is reached.
The no-rate coding at the user is optimized according to the network channel state and the compression ratio of the RRH signal, and the specific steps are as follows:
1) for the decoding of the l-th round at the BBU, the LT input node transmits LLR information to the LDPC code pattern check node, and the carried external information is as follows:
Figure BDA0002311027600000091
in the formula
Figure BDA0002311027600000092
Is the average extrinsic information, alpha, passed from the output node to the input node for the l-1 st iteration LTiFor the ratio of input nodes in the LT decoding diagram with degree i, dvAnd J is an extrinsic information function carried by the message which satisfies the symmetric Gaussian distribution. For a message with mean τ and variance 2 τ, which obeys a symmetric gaussian distribution, it contains the extrinsic information:
Figure BDA0002311027600000093
the extrinsic information returned by the LDPC check node to the LT input node is:
Figure BDA0002311027600000094
xi in the formulaiIs the variable node proportion with degree i in the LDPC code graph,
Figure BDA0002311027600000095
is the proportion, d ', of the side connected with the check node of degree j in the LDPC code graph'vIs LDPC code graph variable node maximum degree, d'cAnd checking the maximum degree of the node for the LDPC code graph. The extrinsic information that the LT input node transmits a message to the output node is:
Figure BDA0002311027600000096
in the formula
Figure BDA0002311027600000101
Is the proportion of edges connected to degree i input nodes, dvIs the maximum degree of the input node;
finally, the extrinsic information returned by the LT output node corresponding to the signal with the quantization bit a to the LT input node is:
Figure BDA0002311027600000102
in the formula of omegadRepresenting the proportion of edges connected to the degree dsout node,
Figure BDA0002311027600000103
Ia,γ＝J(ALLRi) Means ALLR representing the mean of the log-likelihood ratios of the signal with the number a of quantization bits at the signal-to-noise ratio γaThe amount of information carried, wherein:
Figure BDA0002311027600000104
where a ═ b or a ═ b +1, the average extrinsic information that all LT output nodes send back to the LT input node is:
Figure BDA0002311027600000105
in the formula YrThe compression rate of the corresponding code word quantization bit number in the quantizer is shown, b is the quantization bit number, r is 1,2 …, b, and the equations (6) and (7) are substituted into (9) to obtain the compression rate of each iteration
Figure BDA0002311027600000106
Update, which can be expressed as oneFunction Φ (·):
Figure BDA0002311027600000107
in the formula
Figure BDA0002311027600000108
Average degree of input nodes for LT code graph, { omega }dIs the coefficient of the degree distribution of the edge of the LT output node.
2) Defining the channel gains of 2 links as a vector
Figure BDA0002311027600000109
The situation of different link values h is expressed as W vectors
Figure BDA00023110276000001010
Vector riIs defined as Pr (Γ)i) The joint optimization problem is listed below:
Figure BDA0002311027600000111
Figure BDA0002311027600000112
where epsilon is a small amount greater than zero,
Figure BDA0002311027600000113
the minimum threshold for the outer information to be correctly decoded,
Figure BDA0002311027600000114
is the channel gain gammaiThe lower signal-to-noise ratio is the theoretical capacity of the gaussian channel of gamma. . Fixing the optimization problem (11)
Figure BDA0002311027600000115
The degree distribution omega (x) of the edge can be solved by a linear programming solution,
Figure BDA0002311027600000116
the average degree of the LT input nodes is found through an exhaustion method.
3) By the formula
Figure BDA0002311027600000117
And (5) converting to obtain the optimal rateless code degree distribution omega (x).

Claims (1)

1. A method for optimizing the distribution of the non-rate code degrees under the compression transmission of a cloud access network is characterized by comprising the following steps:
1) optimizing degree distribution adopted by non-rate coding at a user according to the network channel state and the compression ratio of the RRH signal;
the step 1) specifically comprises the following steps:
1.1) for the l-th round of decoding at the BBU, the LT input node transmits LLR information to the LDPC code graph check node, and the carried external information is as follows:
Figure FDA0003623624570000011
in the formula
Figure FDA0003623624570000012
Is the average extrinsic information, alpha, transmitted from the LT output node to the input node in the 1 st iterationiFor the ratio of input nodes in the LT decoding diagram with degree i, dvInputting the maximum degree of a node for an LT code diagram, wherein J is an external information function carried by a message meeting symmetric Gaussian distribution;
for a message with mean τ and variance 2 τ, which obeys a symmetric gaussian distribution, it contains the extrinsic information:
Figure FDA0003623624570000013
the extrinsic information returned by the LDPC check node to the LT input node is:
Figure FDA0003623624570000014
xi in the formulaiIs the variable node proportion with degree i in the LDPC code graph,
Figure FDA0003623624570000015
is the proportion of edges connected with a check node of degree j in the LDPC code graph, d'vIs LDPC code graph variable node maximum degree, d'cChecking the maximum degree of the node for the LDPC code graph;
the external information that the LT input node transmits a message to the output node is:
Figure FDA0003623624570000016
in the formula
Figure FDA0003623624570000017
Is the proportion of edges connected to degree i input nodes, dvIs the maximum degree of the input node;
finally, the extrinsic information returned by the LT output node corresponding to the signal with the quantization bit a to the LT input node is:
Figure FDA0003623624570000021
in the formula of omegadRepresenting the proportion of edges connected to the degree dsout node,
Figure FDA0003623624570000022
Ia,γ＝J(ALLRi) Log likelihood ratio average ALLR of signal with quantization bit number a under signal-to-noise ratio gammaaThe amount of information carried, wherein:
Figure FDA0003623624570000023
where a ═ b or a ═ b +1, the average extrinsic information returned by all LT output nodes to the LT input node is:
Figure FDA0003623624570000024
in the formula YrThe compression rate of the corresponding code word quantization bit number in the quantizer is shown, b is the quantization bit number, r is 1,2 …, b, and the equations (4) and (5) are substituted into (7) to obtain the compression rate of each iteration
Figure FDA0003623624570000025
Update, which can be expressed as a function Φ (·):
Figure FDA0003623624570000026
in the formula
Figure FDA0003623624570000027
Average degree of input nodes, { omega, { for LT code graphdThe coefficient of the degree distribution of the edge of the LT output node;
1.2) defining the channel gains of 2 links as a vector
Figure FDA0003623624570000028
The situation of different link values h is expressed as W vectors
Figure FDA0003623624570000029
Vector ΓiIs defined as Pr (Γ)i) The joint optimization problem is listed as follows:
Figure FDA00036236245700000210
Figure FDA0003623624570000031
where epsilon is a small amount greater than zero,
Figure FDA0003623624570000032
the minimum threshold for the outer information to be correctly decoded,
Figure FDA0003623624570000033
is channel gain gammaiThe lower signal-to-noise ratio is the theoretical capacity of a Gaussian channel with gamma; fixing the optimization problem (11)
Figure FDA0003623624570000034
The degree distribution omega (x) of the edge can be solved by a linear programming solution,
Figure FDA0003623624570000035
finding the average degree of LT input nodes by an exhaustion method;
1.3) by the formula
Figure FDA0003623624570000036
The optimal rate-free code degree distribution omega (x) is obtained through conversion;
2) the user carries out non-rate coding on the original information according to degree distribution, and the code words are sent to each RRH covering the user after being modulated; the RRH firstly preprocesses the received signal to become a baseband signal, and then carries out quantization coding compression sending on the signal; the BBU receives the quantized compressed signals sent by the RRHs through the high-speed link, decodes the quantized compressed signals to recover the quantized signals, and finally decodes the quantized signals on a no-rate decoding graph by using a belief propagation algorithm to recover user information;
the step 2) specifically comprises the following steps:
2.1) the channel from the user to the RRH is block fading and remains unchanged in a round of received code words, with single user in the systemTwo RRH uplink transmission, the user uses the original information as the pre-coding of the non-rate code through the LDPC pre-coder in sequence, and then the original information passes through the LT coder, and the distribution omega (x) is omega according to the LT code degree distribution1x+Ω2x2+...+ΩDxD，ΩkD is the probability of degree k, randomly selecting a degree k for each coded bit c, selecting k values with equal probability from all precodes, performing modulo-two summation on the selected k precoded bits to generate a rateless code c, and continuously generating the rateless code c according to the steps1,c2,……,cN；
2.2) mapping the bits 0 and 1 of the non-rate code into a sending symbol x according to the actual modulation mode1,x2,……,xNSending to each RRH covering the user through an antenna;
2.3) the preprocessor of each RRH preprocesses the received signal to obtain a baseband signal: y isi＝hix+niWherein h isiRepresenting source to RRHiChannel gain coefficient of the link between, niRepresents RRHiReceiving noise; then, the quantizer of the RRH quantizes the signal, and the number of quantization levels satisfies 2M-2 according to the forward link capacity b bits/symbol between the RRH and the BBUbWhere b is the quantization bit, the quantization interval is Δ, and the quantization threshold is
Figure FDA0003623624570000041
The quantized signal is
Figure FDA0003623624570000042
The quantization rule is as follows:
Figure FDA0003623624570000043
in the above formula q-M，qk，qMFinger quantized signal
Figure FDA0003623624570000044
Actual quantization level value of;
2.4) each RRH converts the N quantized signals obtained in step 2.3) into binary, b-bit RRHs1The compression rate of the corresponding code word quantization bit number is YrR is 1,2 …, b; the remaining capacity is calculated from the system forward link transmission capacity b
Figure FDA0003623624570000045
Random selection among N quantized signals
Figure FDA0003623624570000046
The signals are quantized by one more bit, and all the signals are sent to the BBU through a high-speed link;
2.5) BBU decoding is divided into two steps, firstly, the compressed quantized signal is decoded to recover RRH1The quantized signal of (a);
2.6) BBU decoding the second step is based on the decompressed quantized signal and the directly transmitted RRH2The quantized signal decodes the code word of the user; user rateless code ciEqual probability of 0 and 1, j-th RRH uploads quantized signal to BBU
Figure FDA0003623624570000047
The soft demodulator of BBU outputs LLR of ith bit as:
Figure FDA0003623624570000048
RRH (resistive random access memory)1And RRH2After the LLRs corresponding to the quantized signals are combined, the LLR of the ith bit is as follows:
Figure FDA0003623624570000049
in the formula,. DELTA.kTo quantize the level qkThe corresponding quantization interval, a is equal to b or b +1,
Figure FDA00036236245700000410
is one by oneVariance of Gaussian noise at RRH, hjA channel gain for the link;
the BBU carries out iterative decoding on a rateless code graph, the 0 th round of iterative decoding, the initial LLR of an input node i in the decoding graph is 0, the initial LLR of an output node is LLR (i), wherein the initial LLR of the input node i in the decoding graph is LLR (i)
Figure FDA0003623624570000051
To quantize the number of bits as b +1,
Figure FDA0003623624570000052
is the number of quantization bits b;
in the first iteration, messages are transmitted from an LT input node to an LDPC check node, the LDPC check node transmits the messages back to the LT input node, the LT input node transmits the messages to an LT output node, and finally the LT output node transmits the messages and LLRs (Log/Log) obtained by calculation according to bit quantization values of corresponding code words back to the LT input node; when the LLR mean value of the input node of the round exceeds the decoding threshold x of the LDPCpThen, iterative decoding is carried out on the LDPC precoding code graph independently;
performing iteration decoding on the 0 th round of the LDPC precoding subgraph, and transmitting LLR (log likelihood ratio) of the input node to the LDPC by the LDPC variable node in the last round of iteration; in the first iteration, the LDPC variable node transmits a message to the LDPC check node, and then the message is transmitted to the LDPC variable node from the LDPC check node;
judging the log-likelihood ratio information LLR(s) of the bit s, judging the information bit s as 0 if the LLR(s) is greater than 0, otherwise judging the information bit s as 1, continuing iteration if the decoding is incorrect according to a judgment output result, and ending the decoding if the decoding is correct or the maximum iteration time t is reached.
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